Psychosocial Risk Assessment in Patients Receiving Ventricular Assist Devices Does not Correlate with Outcomes

Abstract

Background: There are published criteria to optimize patient selection and improve outcomes in patients receiving VAD therapy. Socioeconomic and issues are also explored before ventricular assist device (VAD) placement. However there are no specific psychosocial guidelines to help identify the appropriate VAD patient to maximize outcomes. Therefore, we seek to determine how socioeconomic and psychosocial factors impact this population. Methods: We performed retrospective electronic chart review of 78 consecutive patients who received Ventricular Assist Device Support at our institution from 2009 to 2015. Demographic characteristics, insurance type, income, education level, psychosocial risks and marital status were included in the analysis. The rates of mortality, VAD related infection, and readmission were compared. We used SPSS to calculate Pearson’s Chi square analysis to compare categorical variables and an independent samples T-test for continuous variables. All patients were risk-assessed by a specially trained social-work team prior to surgery and were given low, intermediate or high risk scores. We did Kaplan-Meier Curves to evaluate survival. Results: Our study population consisted of 56 (70%) males. The population consisted of 32 (40%) white, 35 (43.8%) black, 7 (8.8%) Hispanic, and 6(7.5%) other races. Ten (12.5%) had less than high school education, 24 (30%) had high school equivalent education, 14 (17.5%) had higher education, and 32 (40%) had an unknown education level. Four (5%) were uninsured, 32 (40%) had Medicare, 6 (7.5%) had Medicaid, 30 (37.5%) had private insurance, and 8 (10%) were unknown. Forty (50%) had diabetes, 61 (76.3%) had hypertension, 13 (16.3%) had COPD, 41 (51.2%) had Hyperlipidemia, 43 (53.8%) had renal disease and 46 (57.5%) had known coronary artery disease. All the socioeconomic factors examined and the psychosocial risk score showed no overall effect over survival, infection or re admission rate. Conclusion: In our population, income, education level, psychosocial risk category and, insurance type had no effect on outcomes in patients with VADs. Specific psychosocial guidelines to help better evaluate and risk stratify patients prior to VAD are needed. The appropriate level of social support, education, cognition and other psychosocial aspects that effect outcomes and survival in this patient population need to be better defined.